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The Era of 1-bit LLMs: All Large Language Models are in 1.58 Bits
Paper • 2402.17764 • Published • 625 -
MiniMax-01: Scaling Foundation Models with Lightning Attention
Paper • 2501.08313 • Published • 300 -
Group Sequence Policy Optimization
Paper • 2507.18071 • Published • 309 -
Drivel-ology: Challenging LLMs with Interpreting Nonsense with Depth
Paper • 2509.03867 • Published • 209
Collections
Discover the best community collections!
Collections including paper arxiv:2508.16279
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Training a Foundation Model for Materials on a Budget
Paper • 2508.16067 • Published • 2 -
PosterGen: Aesthetic-Aware Paper-to-Poster Generation via Multi-Agent LLMs
Paper • 2508.17188 • Published • 17 -
AgentFly: Fine-tuning LLM Agents without Fine-tuning LLMs
Paper • 2508.16153 • Published • 154 -
AgentScope 1.0: A Developer-Centric Framework for Building Agentic Applications
Paper • 2508.16279 • Published • 53
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Pass@k Training for Adaptively Balancing Exploration and Exploitation of Large Reasoning Models
Paper • 2508.10751 • Published • 28 -
Reinforcement Pre-Training
Paper • 2506.08007 • Published • 262 -
MCP-Universe: Benchmarking Large Language Models with Real-World Model Context Protocol Servers
Paper • 2508.14704 • Published • 42 -
AgentFly: Fine-tuning LLM Agents without Fine-tuning LLMs
Paper • 2508.16153 • Published • 154
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WebWatcher: Breaking New Frontier of Vision-Language Deep Research Agent
Paper • 2508.05748 • Published • 138 -
WebDancer: Towards Autonomous Information Seeking Agency
Paper • 2505.22648 • Published • 33 -
AgentScope 1.0: A Developer-Centric Framework for Building Agentic Applications
Paper • 2508.16279 • Published • 53
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Describe What You See with Multimodal Large Language Models to Enhance Video Recommendations
Paper • 2508.09789 • Published • 5 -
MM-BrowseComp: A Comprehensive Benchmark for Multimodal Browsing Agents
Paper • 2508.13186 • Published • 18 -
ZARA: Zero-shot Motion Time-Series Analysis via Knowledge and Retrieval Driven LLM Agents
Paper • 2508.04038 • Published • 1 -
Prompt Orchestration Markup Language
Paper • 2508.13948 • Published • 48
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Confidence Is All You Need: Few-Shot RL Fine-Tuning of Language Models
Paper • 2506.06395 • Published • 132 -
Magistral
Paper • 2506.10910 • Published • 65 -
Overclocking LLM Reasoning: Monitoring and Controlling Thinking Path Lengths in LLMs
Paper • 2506.07240 • Published • 7 -
Multiverse: Your Language Models Secretly Decide How to Parallelize and Merge Generation
Paper • 2506.09991 • Published • 55
-
The Era of 1-bit LLMs: All Large Language Models are in 1.58 Bits
Paper • 2402.17764 • Published • 625 -
MiniMax-01: Scaling Foundation Models with Lightning Attention
Paper • 2501.08313 • Published • 300 -
Group Sequence Policy Optimization
Paper • 2507.18071 • Published • 309 -
Drivel-ology: Challenging LLMs with Interpreting Nonsense with Depth
Paper • 2509.03867 • Published • 209
-
WebWatcher: Breaking New Frontier of Vision-Language Deep Research Agent
Paper • 2508.05748 • Published • 138 -
WebDancer: Towards Autonomous Information Seeking Agency
Paper • 2505.22648 • Published • 33 -
AgentScope 1.0: A Developer-Centric Framework for Building Agentic Applications
Paper • 2508.16279 • Published • 53
-
Training a Foundation Model for Materials on a Budget
Paper • 2508.16067 • Published • 2 -
PosterGen: Aesthetic-Aware Paper-to-Poster Generation via Multi-Agent LLMs
Paper • 2508.17188 • Published • 17 -
AgentFly: Fine-tuning LLM Agents without Fine-tuning LLMs
Paper • 2508.16153 • Published • 154 -
AgentScope 1.0: A Developer-Centric Framework for Building Agentic Applications
Paper • 2508.16279 • Published • 53
-
Describe What You See with Multimodal Large Language Models to Enhance Video Recommendations
Paper • 2508.09789 • Published • 5 -
MM-BrowseComp: A Comprehensive Benchmark for Multimodal Browsing Agents
Paper • 2508.13186 • Published • 18 -
ZARA: Zero-shot Motion Time-Series Analysis via Knowledge and Retrieval Driven LLM Agents
Paper • 2508.04038 • Published • 1 -
Prompt Orchestration Markup Language
Paper • 2508.13948 • Published • 48
-
Pass@k Training for Adaptively Balancing Exploration and Exploitation of Large Reasoning Models
Paper • 2508.10751 • Published • 28 -
Reinforcement Pre-Training
Paper • 2506.08007 • Published • 262 -
MCP-Universe: Benchmarking Large Language Models with Real-World Model Context Protocol Servers
Paper • 2508.14704 • Published • 42 -
AgentFly: Fine-tuning LLM Agents without Fine-tuning LLMs
Paper • 2508.16153 • Published • 154
-
Confidence Is All You Need: Few-Shot RL Fine-Tuning of Language Models
Paper • 2506.06395 • Published • 132 -
Magistral
Paper • 2506.10910 • Published • 65 -
Overclocking LLM Reasoning: Monitoring and Controlling Thinking Path Lengths in LLMs
Paper • 2506.07240 • Published • 7 -
Multiverse: Your Language Models Secretly Decide How to Parallelize and Merge Generation
Paper • 2506.09991 • Published • 55